Weighted gene co-expression network analysis to explore the mechanism of heroin addiction in human nucleus accumbens

J Cell Biochem. 2020 Feb;121(2):1870-1879. doi: 10.1002/jcb.29422. Epub 2019 Nov 6.

Abstract

Heroin dependence is a complex behavioral disease, and a chronic encephalopathy with the important feature of relapse. The purpose of the study was to identify the regulatory mechanism of the nucleus accumbens (NAc) in heroin dependence. We used weighted gene co-expression network analysis to analyze the GSE87823 data package, which included 27 heroin users and 22 controls of human NAc tissue. Modules were correlated with basic information of samples and enrichment analyses used to identify biological function and transcription factors and online tools were used to perform the gene ontology of significant genes. We identified one gene module from the total data (blue) and the male data (turquoise), respectively. The overlap genes of top 10 hub genes in significant modules (PRR11, SLC35E1, LPP, ZNF721, ZNF611, LRRFIP1) were selected to identify as candidate genes in the regulation mechanism of NAc in heroin dependence. Then, we accorded the results to further explore that miRNA-hsa-miR-155-5p in male and total may be a potential marker. The candidate genes may serve as novel prognostic markers and treatment targets. Hsa-miR-155-5p may be a promising regulatory point for the treatment of heroin addiction.

Keywords: candidate gene; gene expression; modules; weighted gene co-expression network analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers / analysis*
  • Computational Biology / methods*
  • Gene Expression Profiling
  • Gene Expression Regulation*
  • Gene Ontology
  • Gene Regulatory Networks*
  • Heroin Dependence / genetics*
  • Heroin Dependence / pathology
  • Humans
  • Male
  • MicroRNAs / genetics
  • Nucleus Accumbens / metabolism*

Substances

  • Biomarkers
  • MicroRNAs